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pro vyhledávání: '"Zhou, Shuisheng"'
Fuzzy C-Means (FCM) is a widely used clustering method. However, FCM and its many accelerated variants have low efficiency in the mid-to-late stage of the clustering process. In this stage, all samples are involved in the update of their non-affinity
Externí odkaz:
http://arxiv.org/abs/2302.07060
K-Means algorithm is a popular clustering method. However, it has two limitations: 1) it gets stuck easily in spurious local minima, and 2) the number of clusters k has to be given a priori. To solve these two issues, a multi-prototypes convex mergin
Externí odkaz:
http://arxiv.org/abs/2302.07045
Publikováno v:
In Signal Processing February 2025 227
Publikováno v:
In Neurocomputing 21 January 2025 614
Autor:
Chen, Yuxue1 (AUTHOR) chyuxue@hotmail.com, Zhou, Shuisheng1 (AUTHOR) sszhou@mail.xidian.edu.cn
Publikováno v:
Entropy. Aug2024, Vol. 26 Issue 8, p670. 21p.
Kernel logistic regression (KLR) is a conventional nonlinear classifier in machine learning. With the explosive growth of data size, the storage and computation of large dense kernel matrices is a major challenge in scaling KLR. Even the nystr\"{o}m
Externí odkaz:
http://arxiv.org/abs/2108.08605
Kernel-based clustering algorithm can identify and capture the non-linear structure in datasets, and thereby it can achieve better performance than linear clustering. However, computing and storing the entire kernel matrix occupy so large memory that
Externí odkaz:
http://arxiv.org/abs/2002.02846
Akademický článek
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